Rethinking elastic online scheduling of big data streaming applications over high-velocity continuous data streams-Reference-Cited by-同舟云学术

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Rethinking elastic online scheduling of big data streaming applications over high-velocity continuous data streams

Published:2017-09-27 Issue:2 Volume:74 Page:615-636
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Sun Dawei^ORCID,Yan Hongbin,Gao Shang,Liu Xunyun,Buyya Rajkumar

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Melbourne-Chindia Cloud Computing (MC3) Research Network

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

http://link.springer.com/article/10.1007/s11227-017-2151-2/fulltext.html

Reference34 articles.

1. Eskandari L, Huang Z, Eyers D (2016) P-Scheduler: adaptive hierarchical scheduling in apache storm. In: Proceedings of the Australasian Computer Science Week Multiconference, ACSW 2016, No. 26. ACM Press, New York

2. Sun DW, Zhang GY, Wu CW, Li KQ, Zheng WM (2017) Building a fault tolerant framework with deadline guarantee in big data stream computing environments. J Comput Syst Sci 89:4–23

3. Dayarathna M, Toyotaro S (2013) Automatic optimization of stream programs via source program operator graph transformations. Distrib Parallel Databases 31(4):543–599

4. Alexandrov A, Salzmann A, Krastev G, Katsifodimos A, Markl V (2016) Emma in Action: declarative dataflows for scalable data analysis. In: Proceedings of the 2016 International Conference on Management of Data, SIGMOD 2016. ACM Press, New York, pp 2073–2076

5. Convolbo MW, Chou J (2016) Cost-aware DAG scheduling algorithms for minimizing execution cost on cloud resources. J Supercomput 72(3):985–1012

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